Hi, I am trying to estimate divergence times (of genes) in a gene tree, using dS (synonymous substitution rates). At least I am trying to map substitution numbers to branches, then if it corresponds to time is another question.
I am using complete gene trees from Ensembl (one gene tree at a time), including paralog genes, and the corresponding multiple alignements.
I have run codeml using a _free-ratio branch model_ (
I have trouble understanding if the output is relevant for what I need:
- codeml doesn't actually outputs dS _for each_ branch, but rather a distance matrix, right? (in the file
- Plus, the distance matrix in the
2NG.dSfiles is the result from the Nei-Gojobori (1986) method, but (citing the manual) not MLEs [maximum-likelihood estimates] themselves. So are they just rough estimates but codeml can do better?
- Then what exactly is
2NG.t? Time estimates proportional to dS? [EDIT: found it in the "yn00" section of the manual: "number of nucleotide substitutions per codon", i.e. dS and dN combined]
- Do I need to run
multidivtimesto estimate branch lengths?
PS: I paste here my control file if you need to have a look:
seqfile = ENSGT00790000122969_genes.phy * sequence data file name treefile = ENSGT00790000122969_genes.nwk * tree structure file name outfile = ENSGT00790000122969.mlc * main result file name noisy = 1 * 0,1,2,3,9: how much rubbish on the screen verbose = 1 * 1: detailed output, 0: concise output runmode = 0 * 0: user tree; 1: semi-automatic; 2: automatic * 3: StepwiseAddition; (4,5):PerturbationNNI; -2: pairwise seqtype = 1 * 1:codons; 2:AAs; 3:codons-->AAs CodonFreq = 2 * 0:1/61 each, 1:F1X4, 2:F3X4, 3:codon table ndata = 1 * specifies the number of separate data sets in the file clock = 0 * 0: no clock, unrooted tree, 1: clock, rooted tree aaDist = 0 * 0:equal, +:geometric; -:linear, 1-6:G1974,Miyata,c,p,v,a * 7:AAClasses model = 1 * models for codons: * 0:one, 1:b, 2:2 or more dN/dS ratios for branches * models for AAs or codon-translated AAs: * 0:poisson, 1:proportional, 2:Empirical, 3:Empirical+F * 6:FromCodon, 8:REVaa_0, 9:REVaa(nr=189) NSsites = 0 * 0:one w; 1:neutral; 2:positive selection; 3:discrete; 4:freqs; * 5:gamma; 6:2gamma; 7:beta; 8:beta&w; 9:betaγ * 10:beta&gamma+1; 11:beta&normal>1; 12:0&2normal>1; * 13:3normal>0 icode = 0 * 0:universal code; 1:mammalian mt; 2-11:see below Mgene = 0 * 0:rates, 1:separate; fix_kappa = 0 * 1: kappa fixed, 0: kappa to be estimated kappa = 2.05154 * initial or fixed kappa fix_omega = 0 * 1: omega or omega_1 fixed, 0: estimate omega = 1 getSE = 0 * 0: don't want them, 1: want S.E.s of estimates RateAncestor = 1 * (0,1,2): rates (alpha>0) or ancestral states (1 or 2) Small_Diff = .5e-6 * small value used in the difference approximation of derivatives cleandata = 0 * remove sites with ambiguity data (1:yes, 0:no)? fix_blength = 1 * 0: ignore, -1: random, 1: initial, 2: fixed method = 0 * 0: simultaneous; 1: one branch at a time